69,341 research outputs found

    A trans-diagnostic perspective on obsessive-compulsive disorder

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    © Cambridge University Press 2017. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.Progress in understanding the underlying neurobiology of obsessive-compulsive disorder (OCD) has stalled in part because of the considerable problem of heterogeneity within this diagnostic category, and homogeneity across other putatively discrete, diagnostic categories. As psychiatry begins to recognize the shortcomings of a purely symptom-based psychiatric nosology, new data-driven approaches have begun to be utilized with the goal of solving these problems: specifically, identifying trans-diagnostic aspects of clinical phenomenology based on their association with neurobiological processes. In this review, we describe key methodological approaches to understanding OCD from this perspective and highlight the candidate traits that have already been identified as a result of these early endeavours. We discuss how important inferences can be made from pre-existing case-control studies as well as showcasing newer methods that rely on large general population datasets to refine and validate psychiatric phenotypes. As exemplars, we take 'compulsivity' and 'anxiety', putatively trans-diagnostic symptom dimensions that are linked to well-defined neurobiological mechanisms, goal-directed learning and error-related negativity, respectively. We argue that the identification of biologically valid, more homogeneous, dimensions such as these provides renewed optimism for identifying reliable genetic contributions to OCD and other disorders, improving animal models and critically, provides a path towards a future of more targeted psychiatric treatments.Peer reviewedFinal Published versio

    Anger: the unrecognized emotion in emotional disorders

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    Anger plays a prominent definitional role in some psychological disorders currently widely scattered across DSM‐5 categories (e.g., intermittent explosive disorder, borderline personality disorder). But the presence and consequences of anger in the emotional disorders (e.g., anxiety disorders, depressive disorders) remain sparsely examined. In this review, we examine the presence of anger in the emotional disorders and find that anger is elevated across these disorders and, when it is present, is associated with negative consequences, including greater symptom severity and worse treatment response. Based on this evidence, anger appears to be an important and understudied emotion in the development, maintenance, and treatment of emotional disorders.First author draf

    Cognitive Predictors of Worry in a Non-Clinical Population

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    Although worry is considered to be the key feature of generalised anxiety disorder, it has its own unique properties. The study aimed to investigate the extent to which intolerance of uncertainty, poor problem solving confidence, positive beliefs about worry and negative thinking style, predicted worry, both individually and in combination, once the effects of trait anxiety were removed. Ninety-six university students participated in the study by completing a battery of questionnaires. Results, showed trait anxiety to be the strongest predictor. Further, negative thinking, intolerance of uncertainty and positive beliefs about worry contributed to the prediction of worry individually, beyond the effects of trait anxiety. However, when examined collectively, intolerance of uncertainty and a negative thinking were shown to be superior predictors of worry. The findings support the cognitive processing models of worry and generalised anxiety. The implications of these findings are discussed with reference to future research

    Prevalence and correlates of psychopathic traits in the household population of Great Britain

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    There are no previous surveys of psychopathy and psychopathic traits in representative general population samples using standardized instruments. This study aimed to measure prevalence and correlates of psychopathic traits, based on a two-phase survey using the Psychopathy Checklist: Screening Version (PCL: SV) in 638 individuals, 16-74 years, in households in England, Wales and Scotland. The weighted prevalence of psychopathy was 0.6% (95% CI: 0.2-1.6) at a cut score of 13, similar to the noncriminal/nonpsychiatric sample described in the manual of the PCL: SV. Psychopathy scores correlated with: younger age, male gender; suicide attempts, violent behaviour, imprisonment and homelessness; drug dependence; histrionic, borderline and adult antisocial personality disorders; panic and obsessive-compulsive disorders. This survey demonstrated that, as measured by the PCL: SV, psychopathy is rare, affecting less than 1% of the household population, although it is prevalent among prisoners, homeless persons, and psychiatric admissions. There is a half-normal distribution of psychopathic traits in the general population, with the majority having no traits, a significant proportion with non-zero values, and a severe subgroup of persons with multiple associated social and behavioral problems. This distribution has implications for research into the etiology of psychopathy and its implications for society

    Parenting and child anxiety

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    Improving PSF modelling for weak gravitational lensing using new methods in model selection

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    A simple theoretical framework for the description and interpretation of spatially correlated modelling residuals is presented, and the resulting tools are found to provide a useful aid to model selection in the context of weak gravitational lensing. The description is focused upon the specific problem of modelling the spatial variation of a telescope point spread function (PSF) across the instrument field of view, a crucial stage in lensing data analysis, but the technique may be used to rank competing models wherever data are described empirically. As such it may, with further development, provide useful extra information when used in combination with existing model selection techniques such as the Akaike and Bayesian Information Criteria, or the Bayesian evidence. Two independent diagnostic correlation functions are described and the interpretation of these functions demonstrated using a simulated PSF anisotropy field. The efficacy of these diagnostic functions as an aid to the correct choice of empirical model is then demonstrated by analyzing results for a suite of Monte Carlo simulations of random PSF fields with varying degrees of spatial structure, and it is shown how the diagnostic functions can be related to requirements for precision cosmic shear measurement. The limitations of the technique, and opportunities for improvements and applications to fields other than weak gravitational lensing, are discussed.Comment: 18 pages, 12 figures. Modified to match version accepted for publication in MNRA

    Nonparametric reconstruction of the Om diagnostic to test LCDM

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    Cosmic acceleration is usually related with the unknown dark energy, which equation of state, w(z), is constrained and numerically confronted with independent astrophysical data. In order to make a diagnostic of w(z), the introduction of a null test of dark energy can be done using a diagnostic function of redshift, Om. In this work we present a nonparametric reconstruction of this diagnostic using the so-called Loess-Simex factory to test the concordance model with the advantage that this approach offers an alternative way to relax the use of priors and find a possible 'w' that reliably describe the data with no previous knowledge of a cosmological model. Our results demonstrate that the method applied to the dynamical Om diagnostic finds a preference for a dark energy model with equation of state w =-2/3, which correspond to a static domain wall network.Comment: 10 pages, 5 figures, 2 table

    Substituent effects on absorption spectra of pH indicators: an experimental and computational study of sulfonphthaleine dyes

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    Sulfonphthaleine dyes are an important class of pH indicators, finding applications in novel (textile) sensors. In this paper, we present a combined experimental and theoretical study to elucidate the halochromic behaviour of a large set of sulfonphthaleine compounds. Starting from an experimental analysis consisting of UV-Vis spectroscopy, the pH region and the absorption wavelengths related to the colour shift are obtained and pK(a) values are derived. The effect of the substituents on the pH region can be traced back to their electron donating/withdrawing properties. Time-Dependent Density Functional Theory (TD-DFT) is able to adequately produce the trend in experimental wavelengths. Proton affinities are used to assess the effect of substituents on the pH region. The combination of theory and experiment is able to give a better understanding of the pH sensitivity; the methodology in this work will be useful in future dye design and is applicable to other dye classes as well. (C) 2013 Elsevier Ltd. All rights reserved
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